First-mover advantages of the European Union’s climate change mitigation strategy Panagiotis Karkatsoulis, Pantelis Capros, Panagiotis Fragkos, Leonidas Paroussos and Stella Tsani* ,† E3M Lab, Department of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Politechniou Street, 15 773, Zografou Campus, Athens, Greece SUMMARY This paper assesses the costs and benefits for the European Union (EU) as a first mover in climate change mitigation. Scenarios of EU and global climate action to 2050 are quantified using the GEME3-RD model, a global multi-sectoral computable general equilibrium model with endogenous technology progress and detailed representation of the clean energy technologies. The model includes two-factor learning curves (stock and research and development funding) for clean energy technologies, such as electric vehicles, carbon capture and storage, and renewable and efficient appliances. Funding of research and development is endogenously derived as a production factor enabling productivity improvement. The scenarios compare stylised climate strategies, which are asymmetric by world region and have different emission reduction profiles over time. Assuming that strong climate mitigation action will be undertaken only after 2030, the scena- rios compare two main strategies for the EU: pursuing strong emission reduction unilaterally until 2030 versus deferring action for the period after 2030. Asymmetric climate action by region enables asymmetric innovation and manufacturing of clean energy technologies. The macroeconomic assessment of the climate action strategies does not only depend on costs of clean technologies but also on induced technology progress implying asymmetric effects on manufacturing and trade by region, taking into account spillovers. The model-based projections show clear advantages for the EU as a first mover in climate change mitigation compared with a delaying of climate action until 2030. Delayed climate action until 2030 implies higher gross domestic product losses for the EU compared with unilateral action until 2030. The model finds benefits of early action by the EU driven by activity and progress related to clean energy technologies as the EU can achieve competitive advantages over other world regions pursuing climate action later. Copyright © 2016 John Wiley & Sons, Ltd. KEY WORDS climate change mitigation; macroeconomic assessment of clean energy technologies; economic growth induced by technology progress; computable general equilibrium modelling Correspondence *Stella Tsani, E3M Lab, Department of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Politechniou Street, 15 773, Zografou Campus, Athens, Greece. † E-mail: stellatsani@gmail.com Received 9 June 2015; Revised 27 November 2015; Accepted 2 December 2015 1. INTRODUCTION Despite wide acceptance of the potential threats of global warming on the world economy and welfare, little progress has been made internationally towards coordinated emission reduction actions. In order to mitigate climate change impacts, global emissions must start decreasing from 2020 onwards contrasting business as usual emission increasing trends. The emission reduction pledges submitted by various countries in the context of the proce- dures of the United Nations Framework Convention on Climate Change are strongly asymmetric across the countries. In addition, the pledges are not binding casting thus doubts on the commitment of the participating countries. European Union (EU) has been a leading actor in the global effort to mitigate climate change. EU has already set ambitious climate policies in its energy policy agenda targeting a 20% reduction in greenhouse gases (GHGs) emissions by 2020 and 40% by 2030 relative to the 1990 levels. EU has also established the world’s largest emis- sions trading system (EU-ETS), while member states have already agreed and have undertaken steps at national level with the objectives to reduce GHGs emissions, increase INTERNATIONAL JOURNAL OF ENERGY RESEARCH Int. J. Energy Res. 2016; 40:814–830 Published online 13 January 2016 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/er.3487 Copyright © 2016 John Wiley & Sons, Ltd. 814